Instructions to use Outposts/news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Outposts/news-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Outposts/news-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Outposts/news-classification") model = AutoModelForSequenceClassification.from_pretrained("Outposts/news-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from Outposts/news-classification: direct link, hf CLI and curl.
- Browser
- Download file 82 Bytes
-
https://huggingface.co/Outposts/news-classification/resolve/main/added_tokens.json
- Command line
-
hf download hf://Outposts/news-classification/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/Outposts/news-classification/resolve/main/added_tokens.json
82 Bytes
| { | |
| "[CLS]": 101, | |
| "[MASK]": 103, | |
| "[PAD]": 0, | |
| "[SEP]": 102, | |
| "[UNK]": 100 | |
| } | |